Haptic Simulator for Liver Diagnostics through Palpation
March 08, 2019 Β· Declared Dead Β· π Medicine Meets Virtual Reality
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Felix G. Hamza-Lup, Crenguta M. Bogdan, Adrian Seitan
arXiv ID
1903.03268
Category
cs.HC: Human-Computer Interaction
Citations
8
Venue
Medicine Meets Virtual Reality
Last Checked
4 months ago
Abstract
Mechanical properties of biological tissue for both histological and pathological considerations are often required in disease diagnostics. Such properties can be simulated and explored with haptic technology. Development of cost effective haptic-based simulators and their introduction in the minimally invasive surgery learning cycle is still in its infancy. Receiving pretraining in a core set of surgical skills can reduce skill acquisition time and risks. We present the development of a visuo-haptic simulator module designed to train internal organs disease diagnostics through palpation. The module is part of a set of tools designed to train and improve basic surgical skills for minimally invasive surgery.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted